Meet Ava, AI-Sales Engineer

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Julia Nimchinski: Meet Ava or not there.

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Julia Nimchinski: Welcome to the shop.

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Julia Nimchinski: Have you been there.

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Matt Darrow: Hear me. Okay.

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Julia Nimchinski: Yeah.

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Matt Darrow: Hey, Finn? Fantastic. And I know this is when you get into the later afternoon time slots. We also have to bring some of the energy. We’ve got the 15 min session a pretty exciting topic, and we’ll keep it lively along the way, too, and for those that maybe are tuning in for the 1st time. Haven’t seen me before. 1st of all, Julia. Thanks for having me. I’m Matt Darrow. I’m the co-founder, and CEO of Vivin.

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Matt Darrow: We’ve raised over 130 million from excel Menlo salesforce ventures. Our customers are enterprises that you guys know in the audience, Adp snowflake Dayforce Docusign. And we’ve built the world’s 1st AI sales engineer

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Matt Darrow: to give 24 by 7 coverage to your entire. Go to market team. So before we get to the demo.

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Matt Darrow: I had one simple question for everybody in the audience out there, which is well, what would happen if you took

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Matt Darrow: every ae that you work with, and gave them access to your best se, but that se was always available. Well, a few things would happen. Your ramp time would collapse, and you get a whole lot more deals done a lot faster, too. So why aren’t you doing that?

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Matt Darrow: Well, you’re not doing that because it’s insanely expensive, and it’s impossible to find that many great Esses out there. But with our AI se those outcomes can still be possible just through a radically different approach. So in the next 10 min.

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Matt Darrow: You’re going to see how Kevin, an account executive can move faster on his own and be wildly successful by partnering with an AI se a virtual teammate. So let’s go ahead and get started. And, Julie, I need you to make sure that my screen share is gonna work out appropriately. Here, do you see it says, Hey, Kevin, welcome back to your feet! Is that what you’re seeing out there.

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Julia Nimchinski: Perfect,

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Matt Darrow: All right. Fantastic working with Ava.

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Matt Darrow: Our aisc is like working with your best team member, except Ava is always available, and you onboard ava like you onboard a new hire, and because Ava knows the job that she was hired to do to be a sales engineer, she knows what she wants to learn

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Matt Darrow: about your company, your products, your competition, your customers, in this case doing good discovery, a cornerstone of what great sales engineers bring to the table

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Matt Darrow: and Ava works like a human team member by being able to access the same set of information from your Crm systems like salesforce to collaboration tools like slack to email Google, Microsoft, Google Drive, being able to tap into your conversations through Zoom gong chorus. All these aspects that are available to a human are available to Ava.

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Matt Darrow: and also good old fashioned documentation. So if I’m going to teach Ava about what is it like to do? Great discovery in this case at Vivin. I can also just give her a file and just like a human on boards. She’s gonna review this information and tell me what she’s learned

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Matt Darrow: and the whole point there is that I can course, correct her knowledge and her understanding. In this case, what does it mean to do? Phenomenal discovery at Vivin the questions that we like to ask, the pain that we’re searching for, and she takes all of this information that she’s learning, and she appends it to her knowledge.

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Matt Darrow: This is one of the most important breakthroughs, and coming off of the last session, IP. That Vivin has brought to the table is that we have built the brain.

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Matt Darrow: The large language models are phenomenal tools, but that is not the brain that helps an agent understand how to do the job of a professional. And that’s what we’ve codified at Vivin. We know more about sales engineering than anybody else on the planet. We’ve taken that knowledge to build a brain for an agent that can adapt and learn and apply the skills of being a sales engineer in the context of your organization. And the best part is.

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Matt Darrow: this agent is always a master at their topics. They never forget, and they can rapidly learn and outperform any human out there.

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Matt Darrow: So now let’s go back and get to work with Kevin.

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Matt Darrow: So Kevin, just like any other account executive on the sales team, now has access to tap into this incredible new team member, and my best new team member is going to be proactive and help me out. In this case. Kevin’s got a lot going on a couple meetings coming up on the calendar like this important demo with Hooley.

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Matt Darrow: So the 1st thing that Ava is going to do is just to get me prepped, because if we’re all a little bit clear with ourselves, Kevin probably didn’t do the prep. And the research that he was supposed to do before getting on the call. So who are we talking to? What does this company do? Who do they sell to? What’s up in the news? What have they been talking about recently, but most importantly, because Ava has that brain and that point of view of doing the Se. Job.

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Matt Darrow: She knows what ought to be done in this situation in this case. Well, hey, Kevin, we should be collaborating on the demo. And the story that we’re going to tell to get our point across, so proactively guiding me along the way.

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Matt Darrow: And because Ava has already tapped into all the prior details for Julie, the emails that were sent, the external slack channel that was connected all the prior call recordings from zoom and gong and chorus, and all these other providers she also knows. Well, hey, hold on.

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Matt Darrow: There’s actually a couple things that this customer needs that our products and services don’t do. And she knows that because she has a masterful understanding of the products and services that she was trained on, and applying that with her knowledge in the use case of being an Se. So she’s teeing these up for Kevin says, Hey, before we roll into this pitch in this demo, there’s certain things that are really important that we don’t do. So what do we want to do about that? How do we, partner, to make this the best session possible?

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Matt Darrow: We can either sell around them, we can ignore it, pretend they never existed. Or in this case Kevin’s actually smart enough to know that this 1st gap is kind of a big deal, and if we don’t proactively address it. We’re probably gonna not move this deal forward. So Ava’s gonna take all of this into account and do the work.

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Matt Darrow: Now you could go to Openai and ask a General Llm. To build me a demo script, and you will get something amazing amazingly generic and not very useful at all. But Ava is taking everything that she was trained on for your company, as well as that knowledge of being an Se. And saying, Here’s how we land the key points.

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Matt Darrow: These are the stories that we want to tell. And for every single story, here’s what we’re gonna show, say and do what we’re gonna ask the relevant customer stories, the competitive traps that we’re gonna lay. And we’re not gonna stop with just Ava getting Kevin ready for the call. She’s gonna do the work that’s required to have Kevin have the call in this case. Take this and just turn it into the final asset for the customer.

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Matt Darrow: Build me the actual presentation that I’m going to use in this situation. And this collection of slides had never existed before. With all the content and the context and the talking points as well as the relevant areas of the product to highlight. And when things change, for instance, this

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Matt Darrow: meeting with Juli, the CEO, is now going to attend. Eva also has a point of view that based on that new stakeholder. Well, actually, this presentation is no longer relevant because a C-level person is in attendance. It probably should be less technical and more focused on the outcomes. And that’s okay. She can proactively help with that to take all of this and completely turn it on its head

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Matt Darrow: because she has a point of view. On how do you make it relevant for that type of audience because of her expertise of being a sales engineer. In this case customer stories are gonna have the highest impact, and because Ava is on every single deal and every single interaction. She knows all the prior solutions, all the prior use cases, all the prior customer stories

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Matt Darrow: to know that actually, these are the most relevant that we should highlight. So let’s make this whole presentation about how we’ve helped similar customers completely change the output and the dynamic, and then have a great way to walk into this session.

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Matt Darrow: Lastly, she also knows that what we haven’t done yet.

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Matt Darrow: These are the core discovery questions that Kevin still needs to ask. So we can be building a really really strong sales, use case to ultimately drive this deal home ahead of our competition and ultimately hold the line on discounting when it comes to procurement. Now I want to flash forward, you guys 3 days into the future. So Kevin took all those assets, got on the call. He delivered that amazing presentation. We learned so much from the customer because we asked all the right discovery. So now, what?

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Matt Darrow: Well, now, when Kevin goes with his cup of coffee to sit and work with Ava. There’s something else at his footstep for us to review every single salesperson

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Matt Darrow: at every single company. At the end of the day. Their job is to figure out what is the right solution for this customer. How do I take what they need with what we offer and find that amazing intersection that allows them to select us over anybody else now completely unprompted.

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Matt Darrow: And that’s so critical for Agentic AI. You don’t have to tell this agent what work to do, because she knows what work ought to be done, and she knows that she should be building the solution for Kevin.

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Matt Darrow: and the solution is why you pay an Se. 300 400 $500,000 a year, because it’s that masterful understanding of taking the customer’s goals and challenges, understanding their actual technical requirements of what they need to have happen, and then giving the right recommendation of not only what products that they should be using.

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Matt Darrow: but positioned perfectly for how we’re going to solve their pain.

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Matt Darrow: And because of all the great information Ava has, she also knows the proof points, what are the right testimonials and case studies? And if there are product gaps still outstanding, how are we positioning and selling around those to ensure that this deal can get done, and this customer can be successful. And while that is so much meat of information in the crux of every sales campaign.

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Matt Darrow: there’s also simple things that Ava can help Kevin with, too. Say, an email comes in ad hoc at the finish line from someone in it that just wants to know, how does our Jira integration work? These questions always come up at the finish line. Well, Kevin can just do this on his own. He doesn’t need to schedule a call. He doesn’t need to get somebody else out there, and the best part is all of this information, and all of this knowledge is now memorialized in what Ava knows.

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Matt Darrow: So when this deal closes, all of this information can be accessed by the post sales, team services, and customer success, all of those herky, jerky handoffs, the value points lost in translation, potentially even understanding what was oversold and by whom and what are the key risks to the deal. All of this is now completely taken care of.

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Matt Darrow: So that was a very, very brief 10 min, and we’re barely scratching the surface for all of the things that our AI Se. Can do for your entire go to market team. But if I go back to the very, very 1st question that I asked which was.

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Matt Darrow: well, what would happen if an Se. Could support every single person in your go-to-market, from your Sdr. To your aes to your Esses themselves, and even your Csms. Well, everybody’s ramp time would diminish and vanish, and they would all move a lot faster and independently on their own.

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Matt Darrow: We hope that you want to carry this conversation forward with us at Vivin, who have built the brain of the sales engineer something that only we could accomplish, and put that power in your hands to give you a unique competitive advantage in your market. I welcome you to go to vivin.com forward, slash aise at the end of today’s call and the end of this week and the fantastic summit and get in touch with our team, and we can go ahead and carry the conversation forward.

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Matt Darrow: Julia, I know I’m out of time for the very brief demo. I hope we brought the energy here, too, and for all the folks out there as well. I will be on the panel tomorrow. Talking about how do you apply these agentic tools in general to your full? Go to market stack. We’re deploying agents everywhere at Vivin from top of the funnel Sdr. Functions to our own use of ava as our own aise. So even things that we’re doing on the recruiting side, legal side and support side. So I welcome you to join me on that conversation

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Matt Darrow: as well. And Julie, as always. Thanks for having me.

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Julia Nimchinski: Thanks so much, Matt, such a great demo. We are huge fans of what you’re building over there at Vivin. Got some questions pre-submitted by the community, and I guess one from me. You notice we kind of upped our game with the speakers this time. We’ve got Thomas and Goose.

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Julia Nimchinski: one of the leading venture capitalists and acts red points. Now theory and one of his points in almost all of his presentations. The point that people don’t like to bring up

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Julia Nimchinski: the Roi. The ultimate roi of AI is basically human replacement.

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Julia Nimchinski: So how do you see Vivin coming, you know, into play?

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Julia Nimchinski: Given this trend

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Julia Nimchinski: as last year was kind of a year of experimentation this year people are trying to get more tangible. Roi on AI.

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Julia Nimchinski: What are you seeing.

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Matt Darrow: Yeah, I’ll answer this in a few ways, first, st very directly. That is the promise and the premise of Llms. And Gen. AI. I think that’s what’s so different about this cycle in tech versus.

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Matt Darrow: I would talk about like going from perpetual licenses to cloud is like, Okay, this is like a delivery mechanism or going from desktop to mobile, is a user interface mechanism. What Gen. A is all about is replacing what we do as humans and knowledge workers. I wrote this piece previously that had a really simple 2 by 2 matrix that helped you understand. If you or your role was in the danger zone.

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Matt Darrow: where the Y-axis was simply the complexity of your job. And the X-axis was

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Matt Darrow: the number of live interactions you had with other humans. And if you were at the sort of top right quadrant. You were one of the safer roles, but if you were in the bottom, left, right, you were kind of gone yesterday, and I think that’s the best way to think about it is that AI is ultimately here to disrupt so much of this knowledge work that we do as humans. And the severity that’s gonna have an impact on your role is really where you sit on that matrix. So for us bringing something

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Matt Darrow: like this to market what we found from like a Cro seat.

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Matt Darrow: The value is actually very clearly in speed, velocity, independence. That’s what they want, right? The Cfo. Gives them sort of a bucket of headcount and money to go figure out how to hit the number, and they’re like great. How do I just put the best people on all the deals and do them as fast as possible. Right? That’s what they want. Now, I will say, when projects like this get funded. It happens 2 ways. Either an It organization has an AI fund that they’re using for strategic experimentation, or

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Matt Darrow: that Cro is going to the Cfo. And the case that they’re making is how not investing in the next set of hires is how this is going to be funded. And that’s exactly the conversations that are going down, and how the roi of these projects are being sold, because that is very much where all of this is headed in a big way.

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Julia Nimchinski: One of the questions that really resonated from our community here is

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Julia Nimchinski: which aspects of sales engineering can’t AI replace.

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Matt Darrow: Oh, man, you know there’s a lot of. And even if I think about that complexity grid, the things that AI is phenomenal at are all the detailed nuances of the role of the knowledge of the role. So building incredible solutions, answering technical questions come up with compelling storylines. All of that stuff like AI man that’s great at the things that are hard is

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Matt Darrow: when you and I go see each other in person and like at the end of the day people are going to go put projects on the line because they know that they’re going to be supported with the right people, that they are going to be made successful with. And so much of the Se role is also deeply based on trust of how this is all going to work. And I think those areas are really still human, dependent. Now, I will say, and how we see customers drive this adoption.

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Matt Darrow: Every business has these commercial, high volume segments of the market where nobody’s getting any se love. To begin with, those are phenomenal starting points, and as you move up the chain into enterprise strategic major accounts. You’re normally talking about taking 60 to 80% of the work off of somebody’s plate so they can do the things that AI isn’t great at with a lot of those live, political, human-based interactions.

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Julia Nimchinski: Love it. Another question here. How does Vivin quantify pre-sales? Revenue impact.

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Matt Darrow: Oh, man! Well, that’s that’s like we should spend like another 30 min on that like, here’s a couple of things that come to mind like the the normal. The basic, like bottom of the pyramid of need, is revenue assignment. So like how many deals did you work that closed? I always kind of hated that one for for actually driving strategic decisions on, because it was so basic. You don’t know what the individuals are doing. So I think better metrics to actually figuring out the

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Matt Darrow: health and the sort of the power of your Se. Team are more so things like deal lift. So that’s where, hey, Julia, you tap me into a deal. It was initially forecasted at 150 K. And we close it for 500.

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Matt Darrow: And that’s the area that you really understand how healthy this technical team is doing, because the better they are at solutioning objection handling competitive trap lane. That’s what’s gonna help you sell the right products and services, defend your price against discounting and beat your competition too. So those types of kpis and metrics are a much better health of the system, and I’ll give you the second one. The second one is velocity.

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Matt Darrow: Every se organization out there should be held accountable to how quickly deals move through the funnel because every single rep is dependent. Gerard and I joke about sort of a sprinter at Nike with a big parachute on their back. That’s what happens for great reps. Right? They’re bringing the rest of the organization with them. And this is something that an AI sales engineer can massively accelerate, because you can give all that independence directly to these folks so they can move so much faster on their own.

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Matt Darrow: Basically, everybody out there needs to making sure. Well, what deals are the Esses closing fine. But the things that you really need to be understanding are things like deal, lift and velocity, and those are the most important impact points.

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Julia Nimchinski: Last question, Matt, what are you most excited about when it comes to your roadmap for 2025. And how do you compare it to all of the other Vivin competitors. Alternatives. What’s your thinking here?

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Matt Darrow: Yeah, well, I think the number one thing that I’m most excited about is how we’ve really looked at our AI sales engineer as doing the complete role of a sales engineer. So not doing point solutions that they might do like research over here. Competitive understanding here, filling out an Rfp over here. We’ve really built Ava as the ability to do the full role

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Matt Darrow: and to sit side by side with anybody in Gtm. To help them out. And that’s also what makes us different. So part 2 of your question. But to be like the technical bit of what makes it different is

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Matt Darrow: we’ve built the brain that allows us to actually have our agent do the work. And anybody out there that’s trying to build agents that’s relying on the Llm. To be the brain just not going to work. And I think that’s the big area that we bring massive differentiation as well.

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Julia Nimchinski: Thank you so much, Matt.

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Julia Nimchinski: Where should our people go?

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Julia Nimchinski: Should you share the research you’re referring to, will it? I don’t know. Will will we be replaced? How do I know?

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Matt Darrow: Oh, for this! Well, there’s a lot that we write about on this topic. There’s so much content that we have again going to vivin.com even vivin.com forward, slash aise our resource center. Follow me on, Linkedin. Follow our company on Linkedin. We’re always doing interviews on this topic. Because it’s this brave world that people’s roles are vastly changing because their roles and responsibilities are shifting in big ways.

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Matt Darrow: And we’re always interviewing leaders in sales and sales, engineering and customer success on these topics. As we’re working through this transformation with them.

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Julia Nimchinski: Thank you so much again. And that wraps up today’s session and day. Thank you so much. Everyone, for joining and watching. Please leave your feedback in our slack channel events, all of the communication is happening, not in our general channel, but in the events on ensuring everybody knows. And yeah, we are going to have 2. Another exciting days with Sibo grammarly with again, Matt Darrow, tomorrow agent tech AI.

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Julia Nimchinski: Lots of exciting chats, Demos and just executive conversations.

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Julia Nimchinski: So, yeah, see, you soon.